Generative Evolutionary Anomaly Detection in Dynamic Networks

Jiao, Pengfei; Li, Tianpeng; Xie, Yingjie; Wang, Yinghui; Wang, Wenjun; He, Dongxiao; Wu, Huaming

doi:10.1109/tkde.2021.3129057

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Cited by 4 publications

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“…It labels a query as abnormal if it is an outlier in the embedding space. GEABS [16] leverages historical interactions to fit a custom-made generative model that jointly accounts for community structure and node popularity. It labels a query as abnormal if its community membership is unstable according to the…”

Section: Related Workmentioning

confidence: 99%

MAD: Multi-Scale Anomaly Detection in Link Streams

Bautista,

Brisson,

Bothorel

et al. 2024

Proceedings of the 17th ACM International Conference on Web Search and Data Mining

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Section: Related Workmentioning

confidence: 99%